Extract standard error of the variance component in lme4 package (GLMM).

  If you really want them (with all the warnings about their often being
bad summaries of the uncertainty), http://rpubs.com/bbolker/varwald
gives a fairly straightforward recipe for getting the Wald standard
errors of the random effects standard deviations and correlations.

On 14-10-15 09:49 AM, Steve Walker wrote:

The standard approach is to bootstrap the standard errors with
`bootMer`.  But this can take a long time.

Is there a reason you want standard errors instead of confidence
intervals?  If not, you could try profile confidence intervals.  Here is
an example:

library(lme4)
data(grouseticks)

form <- TICKS~YEAR+scale(HEIGHT)+(1|BROOD)+(1|INDEX)+(1|LOCATION)
(m <- glmer(form, family = "poisson", data = grouseticks))
(cim <- confint(m, oldNames = FALSE))

## ------------------------------------------------------------
## Bootstraping takes a _long_ time, but does give you
## standard errors:
## ------------------------------------------------------------
## (bt <- bootMer(m, function(mm) VarCorr(mm)$BROOD[,], 100))
## sd(bt$t, na.rm = TRUE)
## ------------------------------------------------------------

Cheers,
Steve


On 2014-10-15, 3:29 AM, Mart? Casals wrote:

Dear all,

I?ve fitted  a classical Poisson GLMM with lme4. I obtain the variance

of

random effect (variance component) with the following script:


print(VarCorr(model),comp="Variance")


but I?d like to print the standard error of the variance component. I
think
it is possible with the new version of the lme4 package. How it can be
obtain?



Thanks in advance,


Mart?